9 citations · 13 across the 4 of their papers we have counts for
9 papers
Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang
We consider a setting where multiple entities inter-act with each other over time and the time-varying statuses of the entities are represented as multiple correlated time series.…
Force myography benchmark data for hand gesture recognition and transfer learning
Thomas Buhl Andersen, Rógvi Eliasen, Mikkel Jarlund +1
Force myography has recently gained increasing attention for hand gesture recognition tasks. However, there is a lack of publicly available benchmark data, with most existing studi…
Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes
Jilin Hu, Jianbing Shen, Bin Yang +1
Graph convolutional neural networks~(GCNs) have recently demonstrated promising results on graph-based semi-supervised classification, but little work has been done to explore thei…
PathRank: A Multi-Task Learning Framework to Rank Paths in Spatial Networks
Sean Bin Yang, Bin Yang
Modern navigation services often provide multiple paths connecting the same source and destination for users to select. Hence, ranking such paths becomes increasingly important, wh…
Recurrent Multi-Graph Neural Networks for Travel Cost Prediction
Jilin Hu, Chenjuan Guo, Bin Yang +2
Origin-destination (OD) matrices are often used in urban planning, where a city is partitioned into regions and an element (i, j) in an OD matrix records the cost (e.g., travel tim…
Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results
Razvan-Gabriel Cirstea, Darius-Valer Micu, Gabriel-Marcel Muresan +2
Cyber-physical systems often consist of entities that interact with each other over time. Meanwhile, as part of the continued digitization of industrial processes, various sensor t…